Aktives Lernen von Algorithmen mit interaktiven Visualisierungen

Faltin, Nils

doi:10.1007/978-3-642-58322-3_12

Cited by 7 publications

(15 citation statements)

References 1 publication

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“…A slightly different keyboard layout can be derived for an implementation by Faltin [2000], whose PhD thesis provides a complete analysis of Heapsort and develops an interactive form of learning, programming, simulating and visualizing this algorithm. Two additional keys 'Find (smaller) child' and 'Swap child' realize the Heap condition for a node and its children.…”

Section: Tree Structuresmentioning

confidence: 99%

Algorithm visualization using concept keyboards

Baloian

Breuer

Luther

2005

Proceedings of the 2005 ACM Symposium on Software Visualization

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Software visualization and algorithm animation are topics of growing interest in computer science education. We propose a new interface to support the interaction between learners and the dynamic data structure of standard algorithms. Based on their source code users generate and configure so-called concept keyboards to explore the data structures and to execute the methods of the algorithms. This access is in contrast with a simple step interface which allows visualization of the steps of the algorithm in the right order. The results of the various evaluation phases are given. At this moment a larger study is being undertaken with undergraduates which focuses on the usability of the keyboard. Visualization of algorithmsThere is growing interest in algorithm visualization (AV) to help instructors to explain and learners to understand algorithms. An algorithm animation (AA) shows relevant parameters and variables, the current state and a visual representation of the objects being manipulated and often an animated formal description of the algorithm. Complex model structures are simplified in order to highlight only the important aspects by omitting irrelevant details. A first coarse implementation level only mirrors important strategies like Divide-and-Conquer, Union-Find or Greedy methods. Finer data structures also focus on efficient use of memory implementing the algorithm in place, and during the execution the number of different basic operations like swapping or comparing two objects is accumulated.To achieve better comprehension, the designer scales down data to coarser structures and slows down algorithms that process data.Smooth transitions between different states of moving objects, such as elements inside an array while a sorting algorithm is being performed, can make it easier to follow the way the algorithm works on graphical representations of data structures. In most cases algorithms work only locally on data structures in a serial way. Thus, learners can run the algorithm step by step both forward and backward selecting input parameters, step size and execution speed while interactively exploring a configurable animation of algorithms on their own. The intention of this kind of interactive software is to gain insight into the dynamic behavior of the algorithm.We will not review past AV systems, which are referenced in three books on software visualization edited by John Stasko et al [1998] and Stephan Diehl et al [2000;. Rößling [2003] describes methods of generating animations and classifies known systems.It has been noted that there have been only minor attempts to produce interfaces mirroring the concepts and data structures of the algorithms. In most cases, control and visualization are not separated; thus, interaction uses and modifies the graphic representation of data structures directly. Usually users initialize the visualization by specifying the type of visualization, size of the probe, speed of the animation and granularity of the steps to be executed. During the execution of the animat...

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Section: Tree Structuresmentioning

confidence: 99%

Algorithm visualization using concept keyboards

Baloian

Breuer

Luther

2005

Proceedings of the 2005 ACM Symposium on Software Visualization

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“…Furthermore, various studies, Refs. 19–23 for example, consider the incorporation of pseudo‐code with highlighting to be important for algorithm comprehension. Pseudo‐code offers a more compact way of structuring an algorithm without focusing in the precise syntax of each programming language.…”

Section: A Short Description Of the Visual Linprog Softwarementioning

confidence: 99%

“…A gradual change gives the student more time to observe the altered content. Nowadays, a plethora of researchers agree on the usefulness of smooth transitions, for example, 21, 24, 26, 29.…”

Section: A Short Description Of the Visual Linprog Softwarementioning

confidence: 99%

“…In order for the novice students to avoid confusion, any dynamic presentation should begin with only a small data set for input. Some researchers support that, at most, seven elements should be used, or even changed, in each step 21. This statement emanates from research in psychology, which shows that short‐term memory can store at most five words or figures, six letters, seven colors, and eight digits 25.…”

Section: A Short Description Of the Visual Linprog Softwarementioning

confidence: 99%

“…One single step in an AV system should not be overloaded with many events/processes. From the students' point of view, each step should contain at most one interesting event 21, 26; although intermediary steps could still exist, they should not contain any other interesting event. The approach being supported by Faltin 21 is to present only interesting events.…”

Section: A Short Description Of the Visual Linprog Softwarementioning

confidence: 99%

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An empirical study on factors influencing the effectiveness of algorithm visualization

Lazaridis

Samaras

Sifaleras

2010

Comp Applic In Engineering

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ABSTRACT:The determination of the factors influencing the effectiveness of algorithm visualization poses an interesting research question. In this paper, we present the results of a longitude empirical study regarding this question. The study was based on an evaluation of the Visual LinProg educational tool inside classrooms. Visual LinProg is a web-based educational tool, which solves linear programming problems using animation and visualization techniques. Visual LinProg was developed to be used in linear programming courses to supplement the teaching. Our empirical study is based on questionnaires that include quantitative and qualitative topics. This evaluation first indicates that Visual LinProg facilitates the learning of the revised simplex algorithm and second presents more results on factors influencing the understanding of this algorithm by the students/users of the Visual LinProg.

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Structure and Constraints in Interactive Exploratory Algorithm Learning

Faltin

2002

Software Visualization

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Aktives Lernen von Algorithmen mit interaktiven Visualisierungen

Cited by 7 publications

References 1 publication

Algorithm visualization using concept keyboards

Algorithm visualization using concept keyboards

An empirical study on factors influencing the effectiveness of algorithm visualization

Structure and Constraints in Interactive Exploratory Algorithm Learning

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